Artificial Immune Systems - Models, algorithms and applications

Copyright © 2010 Academic Research Publishing Agency.This article has been made available through the Brunel Open Access Publishing Fund.Artificial Immune Systems (AIS) are computational paradigms that belong to the computational intelligence family and are inspired by the biological immune system. During the past decade, they have attracted a lot of interest from researchers aiming to develop immune-based models and techniques to solve complex computational or engineering problems. This work presents a survey of existing AIS models and algorithms with a focus on the last five years.This article is available through the Brunel Open Access Publishing Fun

Distribuirani obrambeni mehanizmi za clone napade temeljeni na algoritmu za istraživanje gravitacije (GSA) u WSN

Wireless Sensor Networks (WSN) are often deployed in hostile environment and are vulnerable to attacks because of the resource constrained nature of the sensors. Clone attack in WSN is one of the major issues where the messages are eavesdropped, the captured node is cloned, and multiple nodes with same identity are produced by attacker. In order to overcome these issues, in this paper, a Distributed Defense Mechanism for Clone Attacks based on Gravitational Search Algorithm (GSA) in WSN is proposed. For efficiently detecting the suspect nodes, the nodes in the channel can be divided into witness node and the claimer node. The witness nodes are responsible for the suspect nodes detection, whereas the claimer nodes should provide their identities for the detection process. For the witness nodes selection, we utilize the GSA to pick out the best witness nodes set. After selecting the witness nodes, clone attack detection is performed by observing the behavior of the neighbor nodes. On detecting the clone attack, revocation procedure is triggered to revoke the clone attack in the witness nodes. By simulation results, it can be concluded that the proposed algorithm provides better protection to clone attacks by reducing the packet drop and increasing the packet delivery ratio.Bežične senzorske mreže (WSN) često su raspoređene u neprijateljskom okruženju i ranjive su na napade zbog prirode senzora koji su tehnološki ograničeni. Clone napad u WSN jedan je od glavnih problema gdje se poruke prisluškuju, zarobljeni čvor se klonira te napadač proizvede višestruke čvorove istog identiteta. Kako bi nadvladali te probleme, ovaj rad predlaže distribuirani obrambeni mehanizam za clone napade temeljen na algoritmu za istraživanje gravitacije (GSA) u WSN. Kako bi se sumnjivi čvorovi efikasno detektirali, čvorovi u kanalu mogu se podijeliti u čvorove svjedoke i tražene čvorove. Čvorovi svjedoci odgovorni su za otkrivanje sumnjivih čvorova, dok traženi čvorovi trebaju za potrebe procesa detekcije navesti svoj identitet. Za izbor čvorova svjedoka, koristi se GSA kako bi se izabrala grupa čvorova koji su najprikladniji. Nakon izbora čvorova svjedoka, otkivanje clone napada vrši se promatranjem ponašanja susjednih čvorova. Otkrivanjem clone napada aktivira se proces opoziva kako bi se opozvao clone napad u čvorovima svjedocima. Prema rezultatima dobivenim iz simulacije može se zaključiti kako predloženi algoritam pruža bolju zaštitu od clone napada smanjivanjem odbacivanja paketa i povećavanjem omjera isporuke paketa

Establishment of recombinant antibody technologies allowing for the generation of SNAP-tag fusion proteins

Triple negative breast cancer (TNBC's) is a highly aggressive and invasive subtype of breast cancer, typically characterised by the lack of estrogen receptor (ER), progesterone receptor (PR) and Human epidermal growth factor receptor 2 (HER2) with an inexplicable partiality towards African women. The acute heterogenicity and complexity of TNBC tumours, together with a lack of well-defined molecular targets, complicates prognosis of the diseases resulting in patient reliance on traditional therapies, like chemotherapy, radiotherapy, and surgery, which are associated with elevated incidence of adverse effects and relapse. A major contributor to the heterogenicity of TNBCs is the tumour microenvironment which is composed of tumour infiltrating lymphocytes (TILs), tumour cells, healthy cells, and tumour vasculature. TILs have commonly been used as a prognostic marker and show robust predictive value for TNBC. In-depth analysis of the TIL composition within TNBC tumours may provide greatly beneficial information for the development of newer tumour microenvironment changing therapies and could assist doctors in understanding what therapies a particular patient maybe susceptible to. Thus, the diagnosis and therapy of this disease may greatly benefit from improved molecular profiling and patient stratification. Precision medicine seeks to provide such a solution, by dividing patients into subpopulations based on disease-specific profiles. The identification of new molecular targets would provide the basis for development of novel therapies. To this end, one of the major aims of this thesis was to develop a phage display based screening technique which could be utilised to isolate novel TNBC specific cancer antibodies. Once selected these antibodies could be used to generate TNBC specific therapies. Specific monoclonal antibodies (mAbs) and derivatives thereof, have already been established as a revolutionary tool for drug delivery to cancerous cells. Such antibodies have been conjugated to cytotoxic drugs to form antibody-drug conjugates, which may exhibit multiple advantages over their unconjugated counterparts, but their general use in clinical application has been restricted due to developmental deliberations. Historical conjugation strategies used for the generation of ADCs commonly resulted in heterogeneous mixtures of ADC species, with varying drug-to-antibody ratios resulting in unpredictable pharmacologic characteristics and safety profiles. In more recent time, self-labelling tags such as Snaptag have provided a means of developing homogenised recombinant immunotherapeutics. Snaptag is a modified version of a human DNA repair enzyme, O6 - alkylguanine-DNA-alkyltransferase (AGT) which naturally removes alkyl residues from damaged DNA. The enzyme reacts specifically with benzylguanine (BG) derivatives via irreversible transfer of alkyl groups to cysteine residues forming stable end products. In this thesis, Snaptag technology, together with other antibody discovery and manipulation tools was used to develop a methodology allowing for the generation of disease specific fusion proteins. Specifically, these fusion proteins consist of single-chain antibody fragments genetically fused to snaptag, allowing for the generation of recombinant ADCs that could be used as a drug delivery system carrying any BG-modified drug to a disease specific targets. In addition, snaptag interacts with BG in a 1:1 stoichiometry giving rise to homogenised combination products which when fused to a scFv provides a fail-safe target-specific therapeutic option. In addition to antibody conjugates, one of the most promising of all mAb based therapies currently used, are checkpoint inhibitors. In a balanced immune response, immune activation is counteracted with immunoregulatory pathways such as checkpoint inhibition. These negative regulatory pathways are necessary for maintaining tolerance and preventing hyperactivation, and are governed by cell surface, inhibitory receptors known as ‘'checkpoint inhibitors''. Blocking of checkpoint pathways during chronic infections and cancer has been shown to improve T-cell functions leading to reduced viral load and tumour burden. These findings have been translated into clinical application where checkpoint inhibitors, which are monoclonal antibodies targeting CTLA-4, PD1, PD-L1 or other inhibitory ligands, have been used to block these inhibitory interactions. The main intention of this research was to develop a methodology which could be used to generate snaptag based recombinant fusion proteins with potential diagnostic and therapeutic applications. Several snaptag based fusion proteins were developed using the recommended methodology these included fusion proteins targeting breast cancer specific antigen BCK1, checkpoint inhibitors PDL1, B7.1/CD80 (interacts with CTLA-4),and TIL characterising markers CD3, CD4, CD8, CD19 and CD20. In addition, to demonstrate the versatility and robustness of this methodology we sought to develop a snaptag based fusion protein not targeting breast cancer related antigens. Zika virus, an emerging infectious disease, currently lacking specific therapies was chosen for this purpose. An scFv derived from antibodies targeting the the Zika-DIII envelop protein, which is essential to the viral infection cycle was used in the snap fusion protein. The resulting ZIKA-DII-snap fusion protein demonstrated specific binding to zika virus membrane fractions. This research demonstrates the feasibility of using snaptag technology as a state-of-the-art conjugation strategy capable of bypassing the challenges previously associated with using antibodies as an effective delivery system for therapeutic drugs. By combining the applicability of snaptag technology with other antibody isolation and manipulation tools we were able to generate several functional snaptag based recombinant fusion proteins. Establishment of this methodology represents an important first step in generating medically necessary, pharmaceutically acceptable immunoconjugates that is instrumental in shifting general therapy towards a more personalized precision medicine approach

An HIV feedback resistor: auto-regulatory circuit deactivator and noise buffer.

Animal viruses (e.g., lentiviruses and herpesviruses) use transcriptional positive feedback (i.e., transactivation) to regulate their gene expression. But positive-feedback circuits are inherently unstable when turned off, which presents a particular dilemma for latent viruses that lack transcriptional repressor motifs. Here we show that a dissipative feedback resistor, composed of enzymatic interconversion of the transactivator, converts transactivation circuits into excitable systems that generate transient pulses of expression, which decay to zero. We use HIV-1 as a model system and analyze single-cell expression kinetics to explore whether the HIV-1 transactivator of transcription (Tat) uses a resistor to shut off transactivation. The Tat feedback circuit was found to lack bi-stability and Tat self-cooperativity but exhibited a pulse of activity upon transactivation, all in agreement with the feedback resistor model. Guided by a mathematical model, biochemical and genetic perturbation of the suspected Tat feedback resistor altered the circuit's stability and reduced susceptibility to molecular noise, in agreement with model predictions. We propose that the feedback resistor is a necessary, but possibly not sufficient, condition for turning off noisy transactivation circuits lacking a repressor motif (e.g., HIV-1 Tat). Feedback resistors may be a paradigm for examining other auto-regulatory circuits and may inform upon how viral latency is established, maintained, and broken

Mitigating Colluding Attacks in Online Social Networks and Crowdsourcing Platforms

Online Social Networks (OSNs) have created new ways for people to communicate, and for companies to engage their customers -- with these new avenues for communication come new vulnerabilities that can be exploited by attackers. This dissertation aims to investigate two attack models: Identity Clone Attacks (ICA) and Reconnaissance Attacks (RA). During an ICA, attackers impersonate users in a network and attempt to infiltrate social circles and extract confidential information. In an RA, attackers gather information on a target\u27s resources, employees, and relationships with other entities over public venues such as OSNs and company websites. This was made easier for the RA to be efficient because well-known social networks, such as Facebook, have a policy to force people to use their real identities for their accounts. The goal of our research is to provide mechanisms to defend against colluding attackers in the presence of ICA and RA collusion attacks. In this work, we consider a scenario not addressed by previous works, wherein multiple attackers collude against the network, and propose defense mechanisms for such an attack. We take into account the asymmetric nature of social networks and include the case where colluders could add or modify some attributes of their clones. We also consider the case where attackers send few friend requests to uncover their targets. To detect fake reviews and uncovering colluders in crowdsourcing, we propose a semantic similarity measurement between reviews and a community detection algorithm to overcome the non-adversarial attack. ICA in a colluding attack may become stronger and more sophisticated than in a single attack. We introduce a token-based comparison and a friend list structure-matching approach, resulting in stronger identifiers even in the presence of attackers who could add or modify some attributes on the clone. We also propose a stronger RA collusion mechanism in which colluders build their own legitimacy by considering asymmetric relationships among users and, while having partial information of the networks, avoid recreating social circles around their targets. Finally, we propose a defense mechanism against colluding RA which uses the weakest person (e.g., the potential victim willing to accept friend requests) to reach their target